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Weisbach are gratefully acknowledged. I bear full responsibility for all remaining errors. Forecasting Future Volatility from Option Prices Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets. This paper presents two main results. First, approximately half of the forecasting bias in the S&P 500 index (SPX) options market is eliminated by constructing measures of realized volatility from five minute observations on SPX futures rather than from daily closing SPX levels. Second, much of the remaining forecasting bias is eliminated by employing an option pricing model that permits a non-zero market price of volatility risk. It is widely believed that option prices provide the best forecasts of the future volatility of the assets which underlie them. One reason for this belief is that option prices have the ability to impound all publicly available information – including all information contained in the history of past prices – about the future volatility of the underlying assets. A second related reason is that option pricing theory maintains that if an option prices fails to embody optimal forecasts of the future volatility of the underlying asset, a profitable trading strategy should be available whose implementation would push the option price to the level that reflects the best possible forecast of future volatility.

Although it is widely believed that option prices provide the best possible forecasts of the future variance of the assets which underlie them, a large body of empirical evidence concludes that option prices consistently yield biased forecasts of future variance. The prevailing interpretation of these findings is that option investors may be forming unbiased forecasts of the future variance of underlying assets but that these unbiased forecasts fail to get impounded into option prices because of either (1) the difficulty of carrying out the necessary arbitrage strategies that would force the prices to their proper levels, or (2) the availability to market makers of lucrative alternative strategies in which they simply profit from the large bid-ask spreads in the options markets. This interpretation has significant consequences for nearly the entire range of option pricing research, since it implies that non-continuous trading, bid-ask spreads, and other market imperfections substantially influence option prices. This implication is important, both because incorporating these types of market imperfections into option pricing models is much more difficult than, for example, altering the dynamics of the underlying asset and also because it suggests that researchers cannot learn about option investor expectations by filtering option

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We document a new stylized fact regarding the term structure of futures volatility. We show that the relationship between the volatility of futuresprices and the slope of the term structure of prices is non-monotone and ...

This article compares realized Henry Hub spot market prices for natural gas during the three most recent winters with futuresprices as they evolve from April through the following February, when trading for the March contract ends.

On December 14, 2009, the reference-case projections from Annual Energy Outlook 2010 were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in itigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings.

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The noise trader sentiment model of De Long, Shleifer, Summers, and Waldmann (1990a) is applied to futures markets. The theoretical results predict that overly optimistic (pessimistic) noise traders result in market prices that are greater (less) than fundamental value. Thus, returns can be predicted using the level of noise trader sentiment. The null rational expectations hypothesis is tested against the noise trader alternative using a commercial market sentiment index as a proxy for noise trader sentiment. Fama-MacBeth cross-sectional regressions test if noise traders create a systematic bias in futuresprices. The time-series predictability of futures returns using known sentiment levels is tested in a Cumby-Modest market timing framework and a more general causality specification. The empirical results lead to the following conclusions. First, there is no evidence that noise trader sentiment creates a systematic bias in futuresprices. Second, predictable market returns using noise trader sentiment is not characteristic of futures markets in general. Third, futures market returns at weekly intervals are characterized by low-order positive autocorrelation with relatively small autoregressive parameters. In those instances where there is evidence of noise trader effects, it is at best limited to isolated markets and particular specifications. Noise Traders, Market Sentiment, and FuturesPrice Behavior

Speculation is not monolithic; it comes in many forms. A certain level of speculation is required for commodity futures markets to function. On the other hand, certain types of trading activities by speculators may damage ...

The New York Times bestselling author heralds the future of business in Free. In his revolutionary bestseller, The Long Tail, Chris Anderson demonstrated how the online marketplace creates niche markets, allowing products and consumers to connect in ...

This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futuresprices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futuresprices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the cr...

On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO 2005), we once again find that the AEO 2006 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEX-AEO 2006 reference case comparison yields by far the largest premium--$2.3/MMBtu levelized over five years--that we have seen over the last six years. In other words, on average, one would have had to pay $2.3/MMBtu more than the AEO 2006 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO 2005), we once again find that the AEO 2006 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEX-AEO 2006 reference case comparison yields by far the largest premium--$2.3/MMBtu levelized over five years--that we have seen over the last six years. In other words, on average, one would have had to pay $2.3/MMBtu more than the AEO 2006 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we once again find that the AEO 2007 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. Specifically, the NYMEX-AEO 2007 premium is $0.73/MMBtu levelized over five years. In other words, on average, one would have had to pay $0.73/MMBtu more than the AEO 2007 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

On December 9, the reference case projections from ''Annual Energy Outlook 2005 (AEO 2005)'' were posted on the Energy Information Administration's (EIA) web site. As some of you may be aware, we at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk. As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past four years, forward natural gas contracts (e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past four years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation (presuming that long-term price stability is valued). In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2005. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or, more recently (and briefly), http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past four AEO releases (AEO 2001-AE0 2004), we once again find that the AEO 2005 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEXAEO 2005 reference case comparison yields by far the largest premium--$1.11/MMBtu levelized over six years--that we have seen over the last five years. In other words, on average, one would have to pay $1.11/MMBtu more than the AEO 2005 reference case natural gas price forecast in order to lock in natural gas prices over the coming six years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation. Fixed-price renewables obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of six years.

On December 9, the reference case projections from ''Annual Energy Outlook 2005 (AEO 2005)'' were posted on the Energy Information Administration's (EIA) web site. As some of you may be aware, we at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk. As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past four years, forward natural gas contracts (e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past four years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation (presuming that long-term price stability is valued). In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2005. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or, more recently (and briefly), http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past four AEO releases (AEO 2001-AE0 2004), we once again find that the AEO 2005 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEXAEO 2005 reference case comparison yields by far the largest premium--$1.11/MMBtu levelized over six years--that we have seen over the last five years. In other words, on average, one would have to pay $1.11/MMBtu more than the AEO 2005 reference case natural gas price forecast in order to lock in natural gas prices over the coming six years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation. Fixed-price renewables obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of six years.

The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

On December 12, 2007, the reference-case projections from Annual Energy Outlook 2008 (AEO 2008) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof) or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers (though its appeal has diminished somewhat as prices have increased); and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

On December 17, 2008, the reference-case projections from Annual Energy Outlook 2009 (AEO 2009) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof), differences in capital costs and O&M expenses, or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired or nuclear generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers; and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal, uranium, and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

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of AEO 2010 Natural Gas Price Forecast to NYMEX FuturesPrices Date: January 4, 2010 1. Introduction, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better

Variance reduction is of highest importance in financial simulation. In this study, we present a new and simple variance reduction technique for pricing discretely monitored lookback and barrier options. It is based on using the corresponding continuously ... Keywords: Control variate, Option pricing, Path dependent options, Variance reduction

Abstract: Based on a two-country, multi-period general equilibrium model of the spot and futures markets for crude oil, we show that there is no theoretical support for the common view that oil futuresprices are accurate predictors of the spot price in the mean-squared prediction error (MSPE) sense; yet under certain conditions there is support for the view that oil futuresprices are unbiased predictors. Our empirical analysis documents that futures-based forecasts typically are less accurate than the no-change forecast and biased, although the bias is small. Much of the MSPE is driven by the variability of the futuresprice about the expected spot price, as captured by the basis. Empirically, the fluctuations in the oil futures basis are larger and more persistent than fluctuations in the basis of foreign exchange futures. Within the context of our theoretical model, this anomaly can be explained by the marginal convenience yield of oil inventories. We show that increased uncertainty about future oil supply shortfalls under plausible assumptions causes the basis to decline and precautionary demand for crude oil to increase, resulting in an immediate increase in the real spot price that is not necessarily associated with an accumulation of oil inventories. Our main result is that the negative of the basis may be viewed as an index of fluctuations in the price of crude oil driven by precautionary demand for oil. An empirical analysis of this index provides independent evidence of how shifts in market expectations about future oil supply shortfalls affect the spot price of crude oil. Such expectation shifts have been difficult to quantify, yet have been shown to play an important role in explaining oil price fluctuations. Our empirical results are consistent with related evidence in the literature obtained by alternative methodologies.

This thesis reviews how oil price has evolved throughout time since it was discovered and commercially exploited in 1859 in Pennsylvania. Rather than a pure economic study, this thesis illustrates how major historic and ...

This paper has three main objectives. First, the various methodologies that have been developed to explain historical oil price changes and forecast futureprice trends are reviewed and summarized. Second, the paper summarizes recent world oil price forecasts, and, then possible, discusses the methodologies used in formulating those forecasts. Third, utilizing conclusions from the reviews of the modeling methodologies and the recent price forecasts, in combination with an assessment of recent and projected oil market trends, oil price projections are given for the time period 1987 to 2022. The paper argues that modeling methodologies have undergone significant evolution during the past decade as modelers increasingly recognize the complex and constantly changing structure of the world oil market. Unfortunately, at this point in time a consensus about the appropriate methodology to use in formulating oil price forecasts is yet to be reached. There is, however, a general movement toward the opinion that both economic and political factors should be considered when making price projections. Likewise, there is no consensus about future oil price trends. Forecasts differ widely. However, in general, forecasts have been adjusted downwardly in recent years. Further, an overall assessment of the forecasts and recent oil market trends suggests that oil prices will remain constant in real terms for the remainder of the 1980s. Real oil prices are expected to increase by between 2 and 3% during the 1990s and beyond. Forecasters are quick to point out, however, that all forecasts are subject to significant uncertainty. 69 references, 3 figures, 10 tables.

re DOE's NOI re continuation or modification of re DOE's NOI re continuation or modification of Price-Anderson Act Comment re DOE's NOI re continuation or modification of Price-Anderson Act Comments of Kerr-McGee Corporation to the "Notice of Inquiry" by DOE seeking comments to assist in the preparation of a report to Congress concerning the continuation or modification of the Price-Anderson Act (the "Act"). These comments will focus solely on question 25 of the notice -- namely, whether the procedures in the Act governing administrative and judicial proceedings should be modified. 62 Fed. Reg. at 68,277. As you will see, we urge the amendment of the Act to implement Congress' goal of assuring a federal forum for any public liability action arising out of a nuclear incident that is presented to any court within the United States,

Europe's international gas trade may have to mark time while the gas industry determines whether the fuel can remain competitive in the wake of Algeria's recent political victory - a high price for its LNG exports to France. Potential gas buyers will face sellers seeking to emulate the $5.10/million Btu price level. The latest conflict, between Algeria and Italy, is preventing start-up of the completed trans-Mediterranean pipeline. Large gas-price increases across Europe would prompt bulk steam-raisers to move to other fuels; the premium household and commercial markets would not be able to absorb the surplus. If the trend of LNG price parity with crude continues, gas could lose a substantial share of its European market and LNG projects will continue to be abandoned.

This study proposes two methods, (1) a probabilistic method based on historical oil prices and (2) a method based on Gaussian simulation, to model futureprices of oil. With these methods to model future oil prices, we can calculate the ranges of uncertainty in traditional probability indicators based on cash flow analysis, such as net present values, net present value to investment ratio and internal rate of return. We found that conventional methods used to quantify uncertainty which use high, low and base prices produce uncertainty ranges far narrower than those observed historically. These methods fail because they do not capture the "shocks" in oil prices that arise from geopolitical events or supply-demand imbalances. Quantifying uncertainty is becoming increasingly important in the petroleum industry as many current investment opportunities in reservoir development require large investments, many in harsh exploration environments, with intensive technology requirements. Insight into the range of uncertainty, particularly for downside, may influence our investment decision in these difficult areas.

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Oil prices are very volatile. But much of this volatility seems to reflect short-term,transitory factors that may have little or no influence on the price in the long run. Many major investment decisions should be guided ...

Abstract: We provide substantial evidence that the futures market for West Texas Intermediate crude oil increased the short-term volatility of the cash price of crude oil. We show that the variability of prices increased using both published posted prices and transaction prices for producers. This increased volatility in the price of crude oil may reflect information aggregated into the price, an increase the variance of shocks to the price of crude oil, or noise in the futuresprice that affects the cash price. We present evidence from experiments consistent with the interpretation that information aggregation not feasible in a posted-price market can explain at least part of the increase in variance. This evidence supports the proposition that information not previously aggregated into the cash price for crude oil is at least part of the reason for the greater variability of the cash price after the opening of the futures market and provides at least one example in which a futures market increased the volatility of the cash market, and prices became more efficient. JEL classification: G130, G140 Key words: crude oil, futures, posted price, experiments, experimental finance, price discovery, information aggregation

Crude oil is the commodity de jour and its pricing is of paramount importance to the layperson as well as to any responsible government. However, one of the main challenges facing econometric pricing models is the forecasting accuracy. ...

This paper attempts to understand the price dynamics of the North American natural gas market through a statistical survey that includes an analysis of the variables influencing the price and volatility of this energy ...

A Distinctive Energy Policy for Scotland? The Impact of Low Carbon Generation on the FuturePrice Distinctive Energy Policy for Scotland?' explores the emergence of a distinctive energy policy for Scotland and raises the issue of the desirability of any differentiation from UK energy policy. Although

Let's engage in further discussion that provides solutions and details, not just criticisms and assertions. Let's engage in a meaningful dialogue about the conditions where real-time pricing or critical peak pricing with decoupling or the SFV rate design with a feebate is most effective. (author)

The benefits of dynamic pricing methods have long been known in industries, such as airlines, hotels, and electric utilities, where the capacity is fixed in the short-term and perishable. In recent years, there has been an increasing adoption of dynamic ... Keywords: Dynamic pricing; e-commerce; revenue management; inventory

This paper studies pricing of stock options for the case when the evolution of the risk-free assets or bond is stochastic. We show that, in the typical scenario, the martingale measure is not unique, that there are non-replicable claims, and that the martingale prices can vary significantly; for instance, for a European put option, any positive real number is a martingale price for some martingale measure. In addition, the second moment of the hedging error for a strategy calculated via a given martingale measure can take any arbitrary positive value under some equivalent measure. Some reasonable choices of martingale measures are suggested, including a measure that ensures local risk minimizing hedging strategy.

America is very much a divided nation when it comes to politics. That polarization is reflected in the environmental and energy realities currently at play in many states, creating a remarkable divide between more conservative Red States and more liberal Blue States when it comes to the amount of CO{sub 2} emitted into the atmosphere and the price of electricity. These differences pose an enormous obstacle in passing climate change legislation. (author)

This article features a discussion of the production of crude oil in non-OPEC countries compared to OPEC countries and concludes that while OPEC has lost significant market share over a fifteen-year period, it has regained much of that loss over the past five years. Also included is refining netback data as of December 22th for the US Gulf Coast, US West Coast, Singapore, and Rotterdam. Prices and taxes (US$) for fuels in North and South America are also given.

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Future trends in pricing options for wholesale electrical generation are discussed. Specifically, the effect of price derivatives on electricity consumption are examined. Economic analyses are presented for customer demand in real-time pricing scenarios with and without a price derivative hedge. It is determined that consumption will be curtailed even when price caps have been purchased. Consumption behavior is also analyzed to determine the effect of different price caps; regardless of price, consumption is curtailed in response to price.

The price of crude oil in the U.S. had never exceeded $40 per barrel until mid-2004. By 2006 it reached $70 per barrel, and in July 2008 it reached a peak of $145. By the end of 2008 it had plummeted to about $30 before increasing again, reaching about $110 in 2011. Are “speculators ” to blame for at least part of the volatility and sharp run-ups in price? We clarify the potential and actual effects of speculators, and investors in general, on commodity prices. We focus on crude oil, but our approach can be applied to other commodities. We first address the question of what is meant by “oil price speculation, ” and how it relates to investments in oil reserves, oil inventories, or oil price derivatives (such as futures contracts). Next we outline the ways in which one could speculate on oil prices. Finally, we turn to the data, and calculate counterfactual prices that would have occurred from 1999 to 2012 in the absence of speculation. Our framework is based on a simple and transparent model of supply and demand in the cash and storage markets for a commodity. It lets us determine whether speculation as the driver of price changes is consistent with the data on production, consumption, inventory changes, and changes in convenience yields given reasonable elasticity assumptions. We show speculation had little, if any, effect on prices and volatility.

For a clear picture of how oil prices develop, the author steps away from the price levels to which the world is accustomed, and evaluates scientifically. What makes prices jump from one notch to another The move results from a political or economic shock or the perception of a particular position by the futures market and the media. The shock could range from a war or an assassination to a promise of cooperation among OPEC members (when believed by the market) or to speculation about another failure at an OPEC meeting. In the oil market, only a couple of factual figures can provide a floor to the price of oil. The cost of production of oil in the Gulf is around $2 to $3/bbl, and the cost of production of oil (capital and operating costs) in key non-OPEC areas is well under $10/bbl. With some adjustments for transport and quality, a price range of $13/bbl to $16/bbl would correspond to a reasonable sustainable floor price. The reason for prices above the floor price has been a continuous fear of oil supply interruptions. That fear kept prices above the floor price for many years. The fear factor has now almost fully disappeared. The market has gone through the drama of the Iranian Revolution, the Iran-Iraq war, the tanker war, the invasion of Kuwait, and the expulsions of the Iraqis. And still the oil flowed -- all the time. It has become abundantly clear that fears above the oil market were unjustified. Everyone needs to export oil, and oil will flow under the worst circumstances. The demise of the fear factor means that oil prices tend toward the floor price for a prolonged period.

0 0 Notes: Before looking at El Paso gasoline prices, letÂ’s take a minute to look at the U.S. average price for context. Gasoline prices this year, adjusted for inflation, are the lowest ever. Back in March, before prices began to rise ahead of the traditional high-demand season, the U.S. average retail price fell to $1.00 per gallon. Prices rose an average of 7.5 cents, less than the typical seasonal runup, to peak in early June. Since then, prices have fallen back to $1.013. Given recent declines in crude oil and wholesale gasoline prices, we expect retail prices to continue to ease over at least the next few weeks. Since their sharp runup during the energy crises of the 1970Â’s, gasoline prices have actually been non-inflationary. Adjusting the historical prices by the Consumer Price Index, we can see that todayÂ’s

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Oil prices have risen sharply over the last year, leading to concerns that we could see a repeat of the 1970s, when rising oil prices were accompanied by severe recessions and surging inflation. This Economic Letter examines the historical relationship between oil price shocks and inflation in light of some recent research and goes on to discuss what the recent jump in oil prices might mean for inflation in the future. Figure 1 Inflation and the relative price of oil The historical record Figure 1 plots the price of oil relative to the core personal consumption expenditures price index (PCEPI) together with the core PCEPI inflation

I n South Asia scientists are concerned about the future of the monsoon: will it continue to exist of the Asian summer monsoon under future, warmer, planetary conditions. Our research shows that the people also see wider variations, leading to more floods and droughts. The Asian monsoon, like the West

The electricity price duration curve (EPDC) represents the probability distribution function of the electricity price considered as a random variable. The price uncertainty comes both from the demand side and the supply side, since the load varies continuously, ...

Natural gas prices, as well as oil and coal prices, are forecast using an Excel spreadsheet model at this time, natural gas prices are forecast in more detail than oil and coal prices. Residential in the industrial boiler fuel market to help keep natural gas prices low. Continuing declines in coal prices coupled

. Forecast Methods Natural gas prices, as well as oil and coal prices, are forecast using an Excel in more detail than oil and coal prices. Residential and commercial sector retail natural gas prices market to help keep natural gas prices low. Continuing declines in coal prices coupled with improved

8 8 Notes: World oil prices have tripled from their low point in December 1998 to August this year, pulling product prices up as well. But crude prices are expected to show a gradual decline as increased oil production from OPEC and others enters the world oil market. We won't likely see much decline this year, however, as prices are expected to end the year at about $30 per barrel. The average price of WTI was almost $30 per barrel in March, but dropped to $26 in April as the market responded to the additional OPEC production. However, prices strengthened again, averaging almost $32 in June, $30 in July, and $31 in August. The continued increases in crude oil prices indicate buyers are having trouble finding crude oil, bidding higher prices to obtain the barrels available.

PricesPricesPrices U.S. and State prices for wellhead, imports, exports, citygate, and end-use sectors. Percentages of total volume delivered by sector. (monthly, annual). Residential and Commercial Prices by Local Distributors and Marketers Average price of natural gas delivered to residential and commercial consumers by local distribution companies and marketers, and the percent sold by local distribution companies in selected states and DC (annual). Spot and FuturesPrices Henry Hub natural gas spot price and New York Mercantile Exchange futures contract prices for natural gas based on delivery at the Henry Hub in Louisiana (daily, weekly, monthly, annual). Natural Gas Weekly Update Analysis of current price, supply, and storage data; and a weather snapshot.

One of the first places where consumers are feeling the impact of One of the first places where consumers are feeling the impact of this winter's market pressures is in home heating oil prices. This chart shows prices through February 28, the most recent EIA data available. The general level of heating oil prices each year is largely a function of crude oil prices, and the price range over the course of the heating season is typically about 10 cents per gallon. Exceptions occur in unusual circumstances, such as very cold weather, large changes in crude oil prices, or supply problems. Heating oil prices for East Coast consumers started this winter at just over $1 per gallon, but rising crude oil prices drove them up nearly 21 cents through mid-January. With the continuing upward pressure from crude oil markets, magnified by a regional shortfall of heating oil

Slide 2 of 11 Notes: One of the first places where consumers are feeling the impact of this winterÂ’s market pressures is in home heating oil prices. This chart shows prices through February 7, the most recent EIA data available. The general level of heating oil prices each year is largely a function of crude oil prices, and the price range over the course of the heating season is typically about 10 cents per gallon. Exceptions occur in unusual circumstances, such as very cold weather, large changes in crude oil prices, or supply problems. Heating oil prices for East Coast consumers started this winter at just over $1 per gallon, but rising crude oil prices drove them up nearly 21 cents per gallon through mid-January. With the continuing upward pressure from crude oil markets, magnified by a regional shortfall of

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Cheese prices are derived from the USDA Agricultural Marketing Service Market News, the National Agricultural Statistics Service, and the Chicago Mercantile Exchange. This publication explains the process of cheese pricing. It includes information on hauling rates and freight differentials

A NONÂ­GAUSSIAN ORNSTEINÂ­UHLENBECK PROCESS FOR ELECTRICITY SPOT PRICE MODELING AND DERIVATIVES for analytical pricing of electricity forward and futures contracts. Electricity forward and futures contracts to capture the observed dynamics of electricity spot prices. We also discuss the pricing of European call

Although spot coal prices have declined significantly from the peaks reached during 2001, they remain above pre-spike levels. This report provides analysis and perspective on the implications and likely long-term effects of the spike in spot coal prices that occurred in late 2000 and 2001. The report analyzes factors that will continue to exert upward pressure on coal prices over the next several years, key uncertainties relating to the future balance between coal supply and demand, and strategies for ma...

World demand for gas is expected to rocket, yet future natural gas and liquefied natural gas projects remain threatened by the link of gas prices to crude oil prices. This is the main message that emerged from the 19th World Gas Conference in Milan last week. A number of reports predicted regional demand for gas. All foresaw a rise. International Gas Union (IGU), organizer of the conference, and said world natural gas production has continued to rise despite a significant downturn in industrial production. The paper discusses gas demand in Europe, the correlation between oil and gas prices, the natural gas industry in Indonesia, Russia, and southern Europe.

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Notes: Notes: Prices have already recovered from the spike, but are expected to remain elevated over year-ago levels because of the higher crude oil prices. There is a lot of uncertainty in the market as to where crude oil prices will be next winter, but our current forecast has them declining about $2.50 per barrel (6 cents per gallon) from today's levels by next October. U.S. average residential heating oil prices peaked at almost $1.50 as a result of the problems in the Northeast this past winter. The current forecast has them peaking at $1.08 next winter, but we will be revisiting the outlook in more detail next fall and presenting our findings at the annual Winter Fuels Conference. Similarly, diesel prices are also expected to fall. The current outlook projects retail diesel prices dropping about 14 cents per gallon

Lynn Price Lynn Price China Energy Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720 Office Location: 90-2108 (510) 486-6519 LKPrice@lbl.gov Lynn Price is a Staff Scientist and Leader of the China Energy Group of the Energy Analysis and Environmental Impacts Department, Environmental Energy Technologies Division, of Lawrence Berkeley National Laboratory. Ms. Price has a MS in Environmental Science from the University of Wisconsin-Madison and has worked at LBNL since 1990. Ms. Price has been a member of the Intergovernmental Panel on Climate Change, which won the Nobel Peace Prize in 2007, since 1994 and was an author on the industrial sector chapter of IPCC's Fourth Assessment Report on Mitigation of Climate Change. Since 1999, Ms. Price has provided technical assistance to the Energy

AEO2008 defines the world oil price as the price of light, low-sulfur crude oil delivered in Cushing, Oklahoma. Since 2003, both above ground and below ground factors have contributed to a sustained rise in nominal world oil prices, from $31 per barrel in 2003 to $69 per barrel in 2007. The AEO2008 reference case outlook for world oil prices is higher than in the AEO2007 reference case. The main reasons for the adoption of a higher reference case price outlook include continued significant expansion of world demand for liquids, particularly in non- OECD countries, which include China and India; the rising costs of conventional non-OPEC supply and unconventional liquids production; limited growth in non-OPEC supplies despite higher oil prices; and the inability or unwillingness of OPEC member countries to increase conventional crude oil production to levels that would be required for maintaining price stability. EIA will continue to monitor world oil price trends and may need to make further adjustments in future AEOs.

We study competition among a score of firms participating in an online market for a commodity-type memory module. Firms were able to adjust pricescontinuously; prices determined how the firms were ranked and listed (lowest ...

0 0 1 April 2010 Short-Term Energy Outlook Supplement: Probabilities of Possible FuturePrices 1 EIA introduced a monthly analysis of energy price volatility and forecast uncertainty in the October 2009 Short-Term Energy Outlook (STEO). Included in the analysis were charts portraying confidence intervals around the New York Mercantile Exchange (NYMEX) futuresprices of West Texas Intermediate (equivalent to light sweet crude oil) and Henry Hub natural gas contracts. The March 2010 STEO added another set of charts listing the probability of the future realized price exceeding or falling below given price levels (see Figures 1A and 1B for West Texas Intermediate crude oil price probabilities). These charts are also available as spreadsheets allowing users to input their own prices to

OPEC producers, individually or collectively, often make statements regarding the “fair price ” of crude oil. In some cases, the officials commenting are merely affirming the price prevailing in the crude oil market at the time. In many cases, however, we document that they explicitly disagree with the contemporaneous futuresprice. A natural question is whether these “fair price ” pronouncements contain information not already reflected in market prices. To find the answer, we collect “fair price ” statements made between 2000 and 2009 by officials from OPEC or OPEC member countries. Visually, the “fair price ” series looks like a sampling discretely drawn (with a lag) from the daily futures market price series. Formally, we use several methodologies to establish that “fair price ” pronouncements have little influence on the market price of crude oil and that they supply little or no new news to oil futures market participants.

With the fast development of video and voice network applications, CDN (Content Distribution Networks) and P2P (Peer-to-Peer) content distribution technologies have gradually matured. How to effectively use Internet resources thus has attracted more and more attentions. For the study of resource pricing, a whole pricing strategy containing pricing models, mechanisms and methods covers all the related topics. We first introduce three basic Internet resource pricing models through an Internet cost analysis. Then, with the evolution of service types, we introduce several corresponding mechanisms which can ensure pricing implementation and resource allocation. On network resource pricing methods, we discuss the utility optimization in economics, and emphasize two classes of pricing methods (including system optimization and entities' strategic optimizations). Finally, we conclude the paper and forecast the research direction on pricing strategy which is applicable to novel service situation in the near future.

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The Arab oil embargo of 1973 awakened the world to the reality of energy shortages and higher fuel prices. Agriculture in the United States is highly mechanized and thus energy intensive. This study seeks to develop an evaluative capability to readily determine the short-run effect of rising energy prices on agricultural production. The results are measured in terms of demand schedules for each input investigated, net revenue adjustments, cropping pattern shifts, and changes in agricultural output.
The High Plains of Texas was selected as a study area due to the heterogeneous nature of agricultural production in the region and highly energy intensive methods of production employed. The region is associated with a diversity in crops and production practices as well as a high degree of mechanization and irrigation, which means agriculture is very dependent upon energy inputs and, in turn, is significantly affected by energy price changes. The study area was defined by the Texas Agricultural Extension subregions of High Plains II, High Plains III, and High Plains IV. The crops chosen for study were cotton, grain sorghum, wheat, corn, and soybeans. The energy and energy-related inputs under investigation were diesel, herbicide, natural gas, nitrogen fertilizer, and water.
Mathematical linear programming was used as the analytical technique with parametric programming techniques incorporated into the LP model to evaluate effect of varying input price parameters over a specified range. Thus, demand schedules were estimated. The objective function was constructed using variable costs only; no fixed costs are considered. Therefore, the objective function maximizes net revenue above variable costs and thus limits the study to the short run.
The data bases for the model were crop enterprise budgets developed by the Texas Agricultural Extension Service. These budgets were modified to adapt them to the study. Particularly important was the substitution of owner-operated harvesting equipment for custom-harvesting costs. This procedure made possible the delineation of fuel use by crop and production alternative which was necessary information in the accounting of costs. The completed LP model was applied to 16 alternative situations made up of various input and product price combinations which are considered as feasible in the short run future.
The results reveal that diesel consumption would change very little in the short run unless commodity prices simultaneously decline below the lowest prices since 1971 or unless diesel price approaches $2.00 per gallon. Under average commodity price conditions, natural gas consumption would not decline appreciably until the price rose above $4.00 per 1000 cubic feet (mcf). Even when using the least product prices since 1971, natural gas would be consumed in substantial amounts as long as the price was below $1.28 per Mcf. The findings regarding nitrogen indicate that present nitrogen prices are within a critical range such that consumption would be immediately affected by nitrogen price increases.
Water price was considered as the price a farmer can afford to pay for water above pumping and distribution costs. Application of water was defined as the price that would be paid for imported water. Under average commodity price conditions, the study results show that as water price rises from zero dollars to $22 per acre foot there would be less than a 4 percent reduction in consumption. However, as the pricecontinues to rise, consumption would decline dramatically reaching zero at a water price of $71.75 per acre foot.
This study indicates that rising input prices would cause acreage shifts from irrigated to dryland; however, with average commodity prices, these shifts do not occur until diesel reaches $2.69 per gallon, or natural gas sells for $1.92 per Mcf, or nitrogen price is $.41 per pound, or water price reaches $14.69 per acre foot. In general, the first crops that would shift out of production as energy input prices rise woul

5 5 Notes: One of the first places where consumers are feeling the impact of this winterÂ’s market pressures is in home heating oil prices. This chart shows prices for the last four winters, with this yearÂ’s prices shown through January 24, the most recent EIA data available. The general level of heating oil prices each year is largely a function of crude oil prices, and the price range over the course of the heating season is typically about 10 cents per gallon. Exceptions occur in unusual circumstances, such as very cold weather, large changes in crude oil prices, or supply problems. Although heating oil prices for consumers started this winter at similar levels to those in 1997, they already rose nearly 20 cents per gallon through mid-January. With the continuing upward pressure from crude

The central question for current USEC holders is the extent to which DOE`s prices will increase in the future and whether those prices will be competitive with other sources available at the time of delivery. DOE`s current point of view (as expressed to the US Congress) is that prices will be kept at the ceiling price under the contract. Speculation on the future of DOE`s enrichment enterprise is on the agenda of many utilities this month, as USEC customers must provide notice to DOE on April 1, 1989 if they wish to reduce their contractual commitment in FY 1999 to below 70 percent of their requirements without penalty. The USEC also allows customers to adjust between 70 and 100 percent of their requirements with five years` notice. Based on projected prices for deliveries under the IP2 offer, customers which previously rejected IP2 will probably elect to take only 70 percent of their requirements from DOE in FY 1994. If firm notification is not given for the base SWU requirements, a USEC holder is not rules out as a DOE customer for that year, but DOE cannot guarantee to have the production capacity available. On the other hand, DOE has very aggressively pursued utilities with unfilled requirements in the short term. Given the expected glut of enrichment capacity well into the next decade, the potential for higher DOE prices due to environmental and decommissioning costs at their diffusion plants, and the potential for other suppliers to provide advanced technology, it may prove difficult for DOE to continue to convince its customers that ten-year contracts are in their best interests.

I show that relative levels of aggregate consumption and personal oil consumption provide an excellent proxy for oil prices, and that high oil prices predict low future aggregate consumption growth. Motivated by these facts, I add an oil consumption good to the long-run risk model of Bansal and Yaron [2004] to study the asset pricing implications of observed changes in the dynamic interaction of consumption and oil prices. Empirically I observe that, compared to the first half of my 1987- 2010 sample, oil consumption growth in the last 10 years is unresponsive to levels of oil prices, creating an decrease in the mean-reversion of oil prices, and an increase in the persistence of oil price shocks. The model implies that the change in the dynamics of oil consumption generates increased systematic risk from oil price shocks due to their increased persistence. However, persistent oil prices also act as a counterweight for shocks to expected consumption growth, with high expected growth creating high expectations of future oil prices which in turn slow down growth. The combined effect is to reduce overall consumption risk and lower the equity premium. The model also predicts that these changes affect the riskiness of of oil futures contracts, and combine to create a hump shaped

Market prices set the value of electric power assets and contracts, yet forward prices are unavailable for time horizons relevant to most valuations. Price forecasts are inherently uncertain because the drivers of prices are uncertain, but equilibrating market forces also work to reduce the growth of uncertainty over time. Consequently, quantifying the degree of futureprice uncertainty is difficult, but has tremendous strategic potential for power companies seeking to value real options and invest in fl...

The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment. Learn about EIA and Energy Department organizations that track energy prices and trends.

In this article we present a continuous time model for natural gas and crude oil futureprices. Its main feature is the possibility to link both energies in the long term and in the short term. For each energy, the future returns are represented as the sum of volatility functions driven by motions. Under the risk neutral probability, the motions of both energies are correlated Brownian motions while under the historical probability, they are cointegrated by a Vectorial Error Correction Model. Our approach is equivalent to defining the market price of risk. This model is free of arbitrage: thus, it can be used for risk management as well for option pricing issues. Calibration on European market data and numerical simulations illustrate well its behavior.

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0 0 1 July 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 July 7, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $75.34 per barrel in June 2010 ($1.60 per barrel above the prior month's average), close to the $76 per barrel projected in the forecast in last month's Outlook. EIA projects WTI prices will average about $79 per barrel over the second half of this year and rise to $84 by the end of next year (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown (Energy Price Volatility and Forecast Uncertainty). WTI futures for September 2010 delivery for the

November 2010 November 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 November 9, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged almost $82 per barrel in October, about $7 per barrel higher than the September average, as expectations of higher oil demand pushed up prices. EIA has raised the average fourth quarter 2010 WTI spot price forecast to about $83 per barrel compared with $79 per barrel in last monthÊ¹s Outlook. WTI spot prices rise to $87 per barrel by the fourth quarter of next year. Projected WTI prices average $79 per barrel in 2010 and $85 per barrel in 2011. WTI futures for January 2011 delivery (for the 5-day period ending November 4)

May 2010 May 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 May 11, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $84 per barrel in April 2010, about $3 per barrel above the prior month's average and $2 per barrel higher than forecast in last month's Outlook. EIA projects WTI prices will average about $84 per barrel over the second half of this year and rise to $87 by the end of next year, an increase of about $2 per barrel from the previous Outlook (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

0 0 1 June 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 June 8, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged less than $74 per barrel in May 2010, almost $11 per barrel below the prior month's average and $7 per barrel lower than forecast in last month's Outlook. EIA projects WTI prices will average about $79 per barrel over the second half of this year and rise to $84 by the end of next year, a decrease of about $3 per barrel from the previous Outlook (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

The purpose of this study is to better understand the effects participatory pricing strategies have on consumer perceptions and behaviors in a sport event pricing scenario. Participatory pricing strategies are those that include the consumer in setting the final price of a good or service. These mechanisms include name-your-own-price (NYOP) and pay-what-you-want (PWYW). These pricing strategies are now being introduced into the sport industry. With the increased use of these strategies, and the lack of research in sport management pertaining to consumers’ perceptions of price, specifically consumer voice in price setting, there is a gap in the literature that needs to be filled. This study investigates the consumer’s perceptions of price fairness, perceived value, as well as consumer behavior (i.e. purchase intentions and willingness-to-pay), when encountering participatory pricing strategies. The following dissertation presents a quantitative experimental design, asking subjects to participate in a simulated ticket purchase experience. Difference between experimental groups was assessed based on price fairness, perceived value, willingness-to-pay, and purchase intentions. Results indicate there is a significant difference between participatory pricing groups and traditional fixed price groups when examining price fairness, perceived value, willingness-to-pay, and final average prices paid. Specifically, price fairness evaluations were significantly higher for the PWYW and fixed price groups, and lower for the NYOP group. In addition to the price fairness differences, the groups differed on their evaluations of perceived value (PWYW and fixed are the same, both higher than NYOP). Furthermore, the results reveal that consumers involved in the NYOP mechanism evoked higher levels of willingness-to-pay than PWYW and fixed. Furthermore, the study also found that the final average price paid following the experiment differed based on the mechanism. The PWYW and fixed price mechanisms paid similar amounts, while both of them were significantly higher than the NYOP mechanism. This suggests that while one of the biggest concerns for the PWYW treatment is a low final average price (even $0); this may not be an issue in a sport ticket pricing scenario. Study limitations and future research are included in the following dissertation.

A presentation to the NPRA Annual Meeting discussing the major factors that drove petroleum prices, price differentials, and margins in 2004, and what this might mean for refiners as we look towards the future.

Heightened natural gas prices have emerged as a key energy-policy challenge for at least the early part of the 21st century. With the recent run-up in gas prices and the expected continuation of volatile and high prices in the near future, a growing number of voices are calling for increased diversification of energy supplies. Proponents of renewable energy and energy efficiency identify these clean energy sources as an important part of the solution. Increased deployment of renewable energy (RE) and energy efficiency (EE) can hedge natural gas price risk in more than one way, but this paper touches on just one potential benefit: displacement of gas-fired electricity generation, which reduces natural gas demand and thus puts downward pressure on gas prices. Many recent modeling studies of increased RE and EE deployment have demonstrated that this ''secondary'' effect of lowering natural gas prices could be significant; as a result, this effect is increasingly cited as justification for policies promoting RE and EE. This paper summarizes recent studies that have evaluated the gas-price-reduction effect of RE and EE deployment, analyzes the results of these studies in light of economic theory and other research, reviews the reasonableness of the effect as portrayed in modeling studies, and develops a simple tool that can be used to evaluate the impact of RE and EE on gas prices without relying on a complex national energy model. Key findings are summarized.

The decline in oil prices has slowed drilling activity at Prudhoe Bay even while offshore field construction work continues. By winter, the layoff of about 14 drilling rigs will mean unemployment for an estimated 1400 workers at one field. New construction projects include a plant to process natural gas liquids for the trans-Alaska pipeline and a miscible injection project. The potential of the limestone reservoir at the Lisburne field will remain an unknown until information is available on the effects of gas injection and waterflooding. The author describes work in progress at Lisburne, Kuparuk River, Endicott, and Milne Point Fields to illustrate the bleak prospects for North Slope development. Higher prices in the future, however, will leave the US with large reserves to develop if the companies can weather the lean years. 1 figure.

Rapid increases in consumer food price beginning in 2007 generated interest in identifying the main factors influencing these increases. In subsequent years, food prices have fluctuated, but generally have continued their ascent. The effects of crude oil, gasoline, corn, and ethanol prices, as well as, the relative foreign exchange rate of the U.S. dollar and producer price indexes for food manufacturing and fuel products on domestic food prices are examined. Because the data series are non-stationary and cointegrated, a vector error correction model is estimated. Weak exogeneity and exclusion tests in the cointegration space are performed. Directed acyclical graphs are used to specify contemporaneous causal relationships. Dynamic interactions among the series are given by impulse response functions and forecast error variance decompositions. Weak exogeneity tests indicate all eight series work to bring the system back into equilibrium following a shock to the system. Further, exclusion tests suggest crude oil, gasoline, food CPI, ethanol, and food PPI variables are not in the long-run relationships. Dynamic analyses suggest the following relationships. Ethanol price is not a major factor in domestic food prices, suggesting that food prices are largely unaffected by the recent increased use of corn-based ethanol for fuel. Crude oil prices, corn prices, and the relative foreign exchange rate of the U.S. dollar, however, do influence domestic food prices with corn price contributing the most to food price variability. Innovation accounting inferences are robust to potential different contemporaneous causal specifications.

il prices have been increasing at an alarming rate since the start of the year. From an average retail price for diesel and unleaded gas of P16.50/liter and P20.90/liter respectively in January, prices have averaged about P19.70/liter and P25.20/liter respectively as of June 8, 2004. These increases represent a jump in oil prices this year of about 20%. The 90 centavo increase in June is the seventh round of increase since January this year. The increase of one peso in May was the biggest since the P1.20 increase made in September 2000 when world crude oil prices rose by 13%. Cause of Rising Prices These recent increases in fuel prices have been attributed mainly to the rising world prices of crude oil. The price of oil has been steadily climbing since September 2003 and countries across the globe have been scrambling to address the apparent inequality between the supply and demand of oil. The expected higher demand for oil in China and the United States (US), due to increased economic activity in both countries, continues to drive up oil prices in the world market. Further, the Organization of Petroleum Exporting Countries (OPEC) imposed a production cut last April 2004 in order to keep price levels floating between US$25 and US$35 per barrel. Low supply levels were further compounded by a decrease in refinery output in the US in May 2004.

The effects of Federal refined-product price controls upon the price of motor gasoline in the United States through 1977 are examined. A comparison of domestic and foreign gasoline prices is made, based on the prices of products actually moving in international trade. There is also an effort to ascribe US/foreign market price differentials to identifiable cost factors. Primary emphasis is on price comparisons at the wholesale level, although some retail comparisons are presented. The study also examines the extent to which product price controls are binding, and attempts to estimate what the price of motor gasoline would have been in the absence of controls. The time period under consideration is from 1969 through 1977, with primary focus on price relationships in 1970-1971 (just before US controls) and 1976-1977. The foreign-domestic comparisons are made with respect to four major US cities, namely, Boston, New York, New Orleans, and Los Angeles. 20 figures, 14 tables.

December 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 December 7, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged over $84 per barrel in November, more than $2 per barrel higher than the October average. EIA has raised the average winter 2010-2011 period WTI spot price forecast by $1 per barrel from the last monthÊ¹s Outlook to $84 per barrel. WTI spot prices rise to $89 per barrel by the end of next year, $2 per barrel higher than in the last Outlook. Projected WTI prices average $79 per barrel in 2010 and $86 per barrel in 2011. WTI futures for February 2011 delivery during the 5-day period ending December 2

October 2010 October 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 October 13, 2010 Release Crude Oil Prices. WTI oil prices averaged $75 per barrel in September but rose above $80 at the end of the month and into early October. EIA has raised the average fourth- quarter 2010 forecasted WTI spot price to $79 per barrel compared with $77 per barrel in last monthÊ¹s Outlook. WTI spot prices are projected to rise to $85 per barrel by the fourth quarter of next year. As has been the case for most of 2010, WTI futures traded with a notable lack of volatility during the third quarter of 2010 (Figure 1). However, prices did bounce in

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1 1 Notes: While EIA cannot claim to explain all of the factors that drive retail gasoline prices, we have had a fair amount of success in exploring the relationship between wholesale and retail prices. In particular, we have looked closely at the "pass-through" of changes in spot prices to the retail market. This graph shows a weighted national average of spot prices for regular gasoline -both conventional and reformulated (shown in red), and EIA's weekly survey price for retail regular (again both conventional and reformulated). As you can see, spot prices tend to be more volatile (and would be even more so on a daily basis), while these changes are smoother by the time they reach the retail pump. Furthermore, by looking at the peaks, you can see the retail prices seem to lag the spot price changes

1 1 1 January 2011 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 January 11, 2011 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged over $89 per barrel in December, about $5 per barrel higher than the November average. Expectations of higher oil demand, combined with unusually cold weather in both Europe and the U.S. Northeast, contributed to prices. EIA has raised the first quarter 2011 WTI spot price forecast by $8 per barrel from last monthÊ¹s Outlook to $92 per barrel with a continuing rise to an average $99 per barrel in the fourth quarter of 2012. The projected annual average WTI price is $93 per barrel in 2011 and $98 per barrel in

As power industry restructuring continues, more and more industry participants will be exposed to financial uncertainties created by locational marginal pricing. These uncertainties differ from those experienced under traditional regulation as well as from the resource adequacy-related price spikes experienced in the Midwest in 1998 and in the West during 2000-2001. Instead, locational marginal pricing systems create uncertainty in the cost of transporting power from resources to loads. This report will ...

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What Is Price Volatility? What Is Price Volatility? The term "price volatility" is used to describe price fluctuations of a commodity. Volatility is measured by the day-to-day percentage difference in the price of the commodity. The degree of variation, not the level of prices, defines a volatile market. Since price is a function of supply and demand, it follows that volatility is a result of the underlying supply and demand characteristics of the market. Therefore, high levels of volatility reflect extraordinary characteristics of supply and/or demand. Prices of basic energy (natural gas, electricity, heating oil) are generally more volatile than prices of other commodities. One reason that energy prices are so volatile is that many consumers are extremely limited in their ability to substitute other fuels when the price, of natural gas

This report presents the results of comprehensive calculations of ceiling and floor prices for natural gas. Ceiling prices are set by the price levels at which it is more economic to switch from natural gas to residual fuel oil in steam units and to distillate in combined cycle units. Switching to distillate is very rare, whereas switching to fuel oil is quite common, varying between winter and summer and increasing when natural gas prices are high or oil prices low. Monthly fuel use was examined for 89 ...

This paper examines the relationship between future carbon prices and the expected profit of companies by case studies with model companies. As the future carbon price will vary significantly in accordance with the political ...

increased rapidly. Excluding food and energy, prices of crude materials and intermediate goods rose at annual rates of 7.2 and 16.7 percent, respectively. At the same time, however, prices of consumer goods and services excluding food and energy increased a more modest 2.9 percent. Many analysts are concerned that recent increases in the prices of crude and intermediate goods may be passed through to consumers, resulting in a higher rate of inflation in consumer prices later this year and perhaps in 1996. This article examines whether price increases at the early stages of production should be expected to move through the production chain, leading to increases in consumer prices. In the first section, a review of basic economic theory suggests there should be a pass-through effect—that is, producer prices should lead and thereby help predict consumer prices. A more sophisticated analysis, though, suggests the pass-through effect may be weak. In the second section, an examination of the empirical evidence indicates that producer prices are not always good predictors of consumer prices. The article Todd E. Clark is an economist at the Federal Reserve Bank of Kansas City. Mangal Goswami, a research associate at the bank, helped prepare the article. concludes that the recent increases in some producer prices do not necessarily signal higher inflation.

Three important imperatives are being pursued by the Commonwealth of Kentucky: ? Developing a viable economic future for the highly trained and experienced workforce and for the Paducah area that today supports, and is supported by, the operations of the US Department of Energy’s (DOE’s) Paducah Gaseous Diffusion Plant (PGDP). Currently, the PGDP is scheduled to be taken out of service in May, 2013. ? Restructuring the economic future for Kentucky’s most abundant indigenous resource and an important industry – the extraction and utilization of coal. The future of coal is being challenged by evolving and increasing requirements for its extraction and use, primarily from the perspective of environmental restrictions. Further, it is important that the economic value derived from this important resource for the Commonwealth, its people and its economy is commensurate with the risks involved. Over 70% of the extracted coal is exported from the Commonwealth and hence not used to directly expand the Commonwealth’s economy beyond the severance taxes on coal production. ? Ensuring a viable energy future for Kentucky to guarantee a continued reliable and affordable source of energy for its industries and people. Today, over 90% of Kentucky’s electricity is generated by burning coal with a delivered electric power price that is among the lowest in the United States. Anticipated increased environmental requirements necessitate looking at alternative forms of energy production, and in particular electricity generation.

For over a century, the US aluminum industry has led the global market with advances in technology, product development, and marketing. Industry leaders recognize both the opportunities and challenges they face as they head into the 21st century, and that cooperative R and D is key to their success. In a unique partnership, aluminum industry leaders have teamed with the US Department of Energy`s Office of Industrial Technologies (OIT) to focus on innovative technologies that will help to strengthen the competitive position of the US aluminum industry and, at the same time, further important national goals. This industry-led partnership, the Aluminum Industry of the Future, promotes technologies that optimize the use of energy and materials in operations and reduce wastes and energy-related emissions. Led by The Aluminum Association, industry leaders began by developing a unified vision of future market, business, energy, and environmental goals. Their vision document, Partnerships for the Future, articulates a compelling vision for the next 20 years: to maintain and grow the aluminum industry through the manufacture and sale of competitively priced, socially desirable, and ecologically sustainable products. Continued global leadership in materials markets will require the combined resources of industry, universities, and government laboratories. By developing a unified vision, the aluminum industry has provided a framework for the next step in the Industries of the Future process, the development of a technology roadmap designed to facilitate cooperative R and D.

Managing Energy Price Risk with Derivatives Managing Energy Price Risk with Derivatives Speaker(s): Douglas Hale Date: September 18, 2003 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Joseph Eto Energy derivatives came into being with the deregulation of the petroleum and natural gas industries in the early 1980s. Although derivatives-forwards, futures and options-have been used in American agriculture since the mid-1800's to manage price risk, they were unnecessary in regulated energy industries. Deregulation revealed that oil, gas and electricity prices are exceptionally volatile. Companies were forced to cope with the uncertainty in energy prices; they latched onto derivatives as one tool for managing that risk. Enron's collapse brought energy derivatives to public attention. Following the derivative linked

to forecast futureprice. As the definitions of these patterns are often subjective, every analyst has a needÂ­ numerable sources of information when faced with the chalÂ­ lenge to forecast future movement of price that patterns can be used to forecast futureprice movement. For example, the famous head

The short-term power exchange offers a glimpse of the deregulated power market. As the electric power industry goes the way of other formerly regulated monopolicies in the United States, incentives will continue to grow for novel ways to trade electricity in hitherto uncharted markets. The emergence of open power markets. The emergence of open power markets thus far has been a patchwork affair. Federally mandated competition in wholesale markets has only recently taken place and all jurisdictional transmission owners must file open access transmission tariffs with the Federal Energy Regulatory Commission. The national agenda has been spotted here and there by state or even utility-specific efforts to unlock retail markets but most of these will take years to implement. Thus, the most common complaint of power market professions is a basic one: It is difficult to determine the market price of electricity. The basic building blocks of an efficient market are missing, e.g. no multitudes of willing buyers and sellers, few arms-length purchases, no price transparency.

The photovoltaic (PV) breakeven price is the PV system price at which the cost of PV-generated electricity equals the cost of electricity purchased from the grid. This point is also called 'grid parity' and can be expressed as dollars per watt ($/W) of installed PV system capacity. Achieving the PV breakeven price depends on many factors, including the solar resource, local electricity prices, customer load profile, PV incentives, and financing. In the United States, where these factors vary substantially across regions, breakeven prices vary substantially across regions as well. In this study, we estimate current and future breakeven prices for PV systems installed on supermarkets in the United States. We also evaluate key drivers of current and future commercial PV breakeven prices by region. The results suggest that breakeven prices for PV systems installed on supermarkets vary significantly across the United States. Non-technical factors -- including electricity rates, rate structures, incentives, and the availability of system financing -- drive break-even prices more than technical factors like solar resource or system orientation. In 2020 (where we assume higher electricity prices and lower PV incentives), under base-case assumptions, we estimate that about 17% of supermarkets will be in utility territories where breakeven conditions exist at a PV system price of $3/W; this increases to 79% at $1.25/W (the DOE SunShot Initiative's commercial PV price target for 2020). These percentages increase to 26% and 91%, respectively, when rate structures favorable to PV are used.

In 1998, pork prices fell to an all time low. Across the industry, concern was expressed for research as to what led to this price crash. Capacity constraints at the packer level have been a key area of concern. This study is an analysis of the effect of capacity constraints on pork prices. Ordinary least squares (OLS) models were run for both live and cutout prices. Capacity constraints were measured three ways: using a binary variable (0,1 dummy) and two continuous variables. One continuous variable was for the number of head slaughtered on the weekend, and the second continuous variable was found by using a ratio of slaughter during the weekends to slaughter during the 5-day workweek ("over-flow" ratio). The continuous variables used to measure capacity constraints were statistically significant explanatory factors in the regressions for hog and pork prices. The capacity constraints were estimated to have a different relationship with the prices at the farm level as compared with packer prices. Increasing capacity constraints is associated with a negative relationship to farm prices, and a positive relationship to packer prices. The measurement used for over-flow ratio, the ratio of weekend slaughter to slaughter during the 5-day workweek, did not generate different results than the continuous variable of weekend slaughter. The estimated coefficients for both continuous variables were more statistically significant than a dummy variable approach for the capacity constraint.

6 6 Notes: On top of the usual factors impacting gasoline prices, natural gas has had some influence recently. MTBE is an oxygenate used in most of the RFG consumed in the U.S. Generally, it follows gasoline prices and its own supply/demand balance factors. But this winter, we saw it respond strongly to natural gas prices. MTBE is made from methanol and isobutylene, which in turn come from methane and butane. Both methane and butane come from natural gas streams. Until this year, the price of natural gas has been so low that it had little effect. But the surge that occurred in December and January pulled MTBE up . Keep in mind that about 11% MTBE is used in a gallon of RFG, so a 30 cent increase in MTBE is only about a 3 cent increase in the price of RFG. While we look ahead at this summer, natural gas prices should be

In 1985, wholesale gasoline prices did not continue the downward trend begun in 1981 despite a continuing decline in crude oil prices. As a result, the spread between these two prices increased in 1985, but only to a level approximating what existed in 1981 and 1982. The Federal Trade Commission investigated two proposed mergers between Texaco, Inc., with Getty Oil Company and Chevron Corporation with Gulf Corporation that had the potential for anticompetitive effects. Using a regression analysis, GAO suggests that increases in concentration at the state level have a positive association with gasoline prices. Because the required divestitures eliminated the increases in concentration exceeding the merger guidelines, GAO believes the two mergers would have had only a small effect on prices.

7 7 Notes: This chart shows the day-to-day volatility in spot crude and heating oil prices, and clearly shows the regional nature of the price spike that occurred last winter. Due to a combination of extreme cold weather, low inventories, and refinery and transportation problems, New York Harbor spot prices shot up as high as $1.77 per gallon in a brief period in late January and early February. In June of this year, distillate spreads had dropped to 2.5 cents per gallon as a result of crude oil prices increasing faster than product prices. But by August spreads had strengthened to about 15 cents, and were as high as 21 cents on average in November 2000, which is almost 15 cents above average -- reflecting continued low stocks and the lack of even a normal summer/autumn build in inventories.

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In this paper we will develop an original approach, based in the use of renewal equations, for obtaining pricing expressions for financial instruments whose underlying asset can be solely described through a simple continuous-time random walk (CTRW). This enhances the potential use of CTRW techniques in finance. We solve these equations for different contract specifications in a particular but exemplifying case. We recover the celebrated results for the Wiener process under certain limits.

7 7 Notes: Retail gasoline prices, like those for distillate fuels, have hit record prices nationally and in several regions this year. The national average regular gasoline price peaked at $1.68 per gallon in mid-June, but quickly declined, and now stands at $1.45, 17 cents higher than a year ago. Two regions, in particular, experienced sharp gasoline price runups this year. California, which often has some of the highest prices in the nation, saw prices peak near $1.85 in mid-September, while the Midwest had average prices over $1.87 in mid-June. Local prices at some stations in both areas hit levels well over $2.00 per gallon. The reasons for the regional price runups differed significantly. In the Midwest, the introduction of Phase 2 RFG was hampered by low stocks,

Nuclear power plants generate approximately 20 percent of U.S. electricity, and the plants in operation today are often seen as attractive assets in the current environment of uncertainty about future fossil fuel prices, high construction costs for new power plants (particularly nuclear plants), and the potential enactment of GHG regulations. Existing nuclear power plants have low fuel costs and relatively high power output. However, there is uncertainty about how long they will be allowed to continue operating.

CHARTER, Price-Anderson Act Task Force CHARTER, Price-Anderson Act Task Force CHARTER, Price-Anderson Act Task Force This charter establishes the responsibilities of the Price-Anderson Act Task Force (Task Force). The Secretary of Energy has approved formation of this Task Force to review the need for the continuation or modification of the Price-Anderson Act, section 170 of the Atomic Energy Act of 1954, as amended (AEA), and to prepare a detailed report for submission to Congress as required by section 170p. of the AEA by August 1, 1998. CHARTER, Price-Anderson Act Task Force More Documents & Publications MEMORANDUM FOR THE SECRETARY Report to Congress on the Price-Anderson Act Appendix A. Notice of Inquiry: Preparation of Report to Congress on Price-Anderson Act. 62 Federal Register 68,272 (December 31, 1997)

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4 of 26 4 of 26 Notes: Spot wellhead prices last summer averaged well over $4.00 per thousand cubic feet during a normally low-price season. During the fall, these prices stayed above $5.00 per thousand cubic feet, more than double the year-ago average price. In January, the spot wellhead price averaged a record $8.98 per thousand cubic feet. Spot prices at the wellhead have never been this high for such a prolonged period. The chief reason for these sustained high gas prices was, and still is, uneasiness about the supply situation. Concern about the adequacy of winter supplies loomed throughout most of the summer and fall as storage levels remained significantly depressed. Last December, the most severe assumptions about low storage levels became real, when the spot price

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Spot pricing covers a range of electric utility pricing structures which relate the marginal costs of electric generation to the prices seen by utility customers. At the shortest time frames prices change every five ...

This study examines the use of OpenADR communications specification, related data models, technologies, and strategies to send dynamic prices (e.g., real time prices and peak prices) and Time of Use (TOU) rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open information model that has been used in California utilities' commercial automated demand response programs since 2007. We find that data models can be used to send real time prices. These same data models can also be used to support peak pricing and TOU rates. We present a data model that can accommodate all three types of rates. For demonstration purposes, the data models were generated from California Independent System Operator's real-time wholesale market prices, and a California utility's dynamic prices and TOU rates. Customers can respond to dynamic prices by either using the actual prices, or prices can be mapped into"operation modes," which can act as inputs to control systems. We present several different methods for mapping actual prices. Some of these methods were implemented in demonstration projects. The study results demonstrate show that OpenADR allows interoperability with existing/future systems/technologies and can be used within related dynamic pricing activities within Smart Grid.

October 2009 October 2009 1 October 2009 Short-Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty 1 Summary It is often noted that energy prices are quite volatile, reflecting market participants' adjustments to new information from physical energy markets and/or markets in energy- related financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the market- clearing process for risk transfer can be used to generate "price bands" around observed futuresprices for crude oil, natural gas, and other commodities. These bands provide a quantitative measure of uncertainty regarding the range in which markets expect prices to

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The main research objective was to answer the following question: Will Consumer Price Index forecast models utilizing computer oil-consumption ratios have better predictive capability as indicated by lower numerical differences from actual results than a model utilizing oil prices as the energy-related variable Multiple linear regressions were run on the components of the United States CPI to reduce them to a kernel set with meaningful predictive capability. New linear regressions were run with this kernel set and crude oil prices during the 1973 to 1984 time period. Crude oil prices were rationalized with a 1972 = 100 based index of GNP base petroleum consumption, the index of net energy imports, and the index of petroleum imports to create new oil substitute constructs to be used in multiple regressions with the CPI. Predictions obtained from the model were compared with actual results in the 1985-1987 time period to determine which model version showed the greatest predictive power. Results of the model tests show that oil prices are strongly related to the CPI, but neither the use of oil prices or the index of GNP-based petroleum consumption produced results that closely predict futureprices.

City Gate City Gate City gate prices represent the total cost paid by gas distribu- tion companies for gas received at the point where the gas is physically transferred from a pipeline company or trans- mission system. This price is intended to reflect all charges for the acquisition, storage, and transportation of gas as well as other charges associated with the LDC's obtaining the gas for sale to consumers. Prices paid at the city gate by local distribution companies rose substantially between 1995 and 1996, climbing from $2.78 per thousand cubic feet to $3.27, an increase of 18 percent. Residential Residential consumers pay the highest price for natural gas. It increased to $6.34 per thousand cubic feet from the 1995 price of $6.06 per thousand cubic feet. However, the 1996 price was 1 percent lower than the 1994 price. In recent years, only modest changes in constant dollars have been

9 9 Notes: One can use a simple model to deal with price/fundamental relationships. This one predicts monthly average WTI price as a function of OECD total petroleum stock deviations from the normal levels . The graph shows the model as it begins predicting prices in 1992. It shows how well the model has predicted not only the direction, but the magnitude of prices over this 8+ year period. While the model is simple and not perfect, it does predict the overall trends and, in particular, the recent rise in prices. It also shows that prices may have over-shot the fundamental balance for a while -- at least partially due to speculative concerns over Mideast tensions, winter supply adequacy, and Iraq's export policies. Prices now seem to be correcting, and may even undershoot briefly

Prompt-Month Energy Futures Prompt-Month Energy FuturesPrices and trading activity shown are for prompt-month (see definition below) futures contracts for the energy commodities listed in the table below. Note that trading for prompt-month futures contracts ends on different dates at the end of the month for the various commodities; therefore, some commodity prices may reference delivery for the next month sooner than other commodity prices. Product Description Listed With Crude Oil ($/barrel) West Texas Intermediate (WTI) light sweet crude oil delivered to Cushing, Oklahoma More details | Contract specifications New York Mercantile Exchange (Nymex) Gasoline-RBOB ($/gallon) Reformulated gasoline blendstock for oxygenate blending (RBOB) gasoline delivered to New York Harbor More details | Contract specifications Nymex

For better or worse, natural gas has become the fuel of choice for new power plants being built across the United States. According to the Energy Information Administration (EIA), natural gas-fired units account for nearly 90% of the total generating capacity added in the U.S. between 1999 and 2005 (EIA 2006b), bringing the nationwide market share of gas-fired generation to 19%. Looking ahead over the next decade, the EIA expects this trend to continue, increasing the market share of gas-fired generation to 22% by 2015 (EIA 2007a). Though these numbers are specific to the US, natural gas-fired generation is making similar advances in many other countries as well. A large percentage of the total cost of gas-fired generation is attributable to fuel costs--i.e., natural gas prices. For example, at current spot prices of around $7/MMBtu, fuel costs account for more than 75% of the levelized cost of energy from a new combined cycle gas turbine, and more than 90% of its operating costs (EIA 2007a). Furthermore, given that gas-fired plants are often the marginal supply units that set the market-clearing price for all generators in a competitive wholesale market, there is a direct link between natural gas prices and wholesale electricity prices. In this light, the dramatic increase in natural gas prices since the 1990s should be a cause for ratepayer concern. Figure 1 shows the daily price history of the 'first-nearby' (i.e., closest to expiration) NYMEX natural gas futures contract (black line) at Henry Hub, along with the futures strip (i.e., the full series of futures contracts) from August 22, 2007 (red line). First, nearby prices, which closely track spot prices, have recently been trading within a $7-9/MMBtu range in the United States and, as shown by the futures strip, are expected to remain there through 2012. These price levels are $6/MMBtu higher than the $1-3/MMBtu range seen throughout most of the 1990s, demonstrating significant price escalation for natural gas in the United States over a relatively brief period. Perhaps of most concern is that this dramatic price increase was largely unforeseen. Figure 2 compares the EIA's natural gas wellhead price forecast from each year's Annual Energy Outlook (AEO) going back to 1985 against the average US wellhead price that actually transpired. As shown, our forecasting abilities have proven rather dismal over time, as over-forecasts made in the late 1980's eventually yielded to under-forecasts that have persisted to this day. This historical experience demonstrates that little weight should be placed on any one forecast of future natural gas prices, and that a broad range of futureprice conditions ought to be considered in planning and investment decisions. Against this backdrop of high, volatile, and unpredictable natural gas prices, increasing the market penetration of renewable generation such as wind, solar, and geothermal power may provide economic benefits to ratepayers by displacing gas-fired generation. These benefits may manifest themselves in several ways. First, the displacement of natural gas-fired generation by increased renewable generation reduces ratepayer exposure to natural gas price risk--i.e., the risk that future gas prices (and by extension future electricity prices) may end up markedly different than expected. Second, this displacement reduces demand for natural gas among gas-fired generators, which, all else equal, will put downward pressure on natural gas prices. Lower natural gas prices in turn benefit both electric ratepayers and other end-users of natural gas. Using analytic approaches that build upon, yet differ from, the past work of others, including Awerbuch (1993, 1994, 2003), Kahn and Stoft (1993), and Humphreys and McClain (1998), this chapter explores each of these two potential 'hedging' benefits of renewable electricity. Though we do not seek to judge whether these two specific benefits outweigh any incremental cost of renewable energy (relative to conventional fuels), we do seek to quantify the magnitude of these two individual benefit

ability to locate, extract, and burn fossil fuels, energy prices are on a long-term up- ward trend [12. Energy price trends have already led data centers to experiment with alter- native energy sources current trends in energy consumption and pricing, we believe that DR is worth exploring in future data

between changing the price p and its consequence on the development of A. The available cash B ... the emerging problem is a non-standard optimal control problem in the sense ...... fed-batch reactor with runaway conditions. ... future technologies, INFORMS, chap Coherent Approaches to Risk in Optimization Under.

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The future of wind power will depend on the ability of the industry to continue to achieve cost reductions. To better understand the potential for cost reductions, this report provides a review of historical costs, evaluates near-term market trends, and summarizes the range of projected costs. It also notes potential sources of future cost reductions. Our findings indicate that steady cost reductions were interrupted between 2004 and 2010, but falling turbine prices and improved turbine performance are expected to drive a historically low LCOE for current installations. In addition, the majority of studies indicate continued cost reductions on the order of 20%-30% through 2030. Moreover, useful cost projections are likely to benefit from stronger consideration of the interactions between capital cost and performance as well as trends in the quality of the wind resource where projects are located, transmission, grid integration, and other cost variables.

Forward Price Forecasting for Power Market Valuation (TR-111860, 1998) presented the basic theory on the market price of risk. However, continued development of the power market has led to additional complexities when applying the concept to electric power. This current report updates that earlier report based on subsequent development of the theory by EPRI and others and reflects two additional years of market data.

Uranium prices hit eight-year highs in both market tiers, $16.60/lb U{sub 3}O{sub 8} for non-former Soviet Union (FSU) origin and $15.50 for FSU origin during mid 1996. However, they declined to $14.70 and $13.90, respectively, by the end of the year. Increased uranium pricescontinue to encourage new production and restarts of production facilities presently on standby. Australia scrapped its {open_quotes}three-mine{close_quotes} policy following the ouster of the Labor party in a March election. The move opens the way for increasing competition with Canada`s low-cost producers. Other events in the industry during 1996 that have current or potential impacts on the market include: approval of legislation outlining the ground rules for privatization of the US Enrichment Corp. (USEC) and the subsequent sales of converted Russian highly enriched uranium (HEU) from its nuclear weapons program, announcement of sales plans for converted US HEU and other surplus material through either the Department of Energy or USEC, and continuation of quotas for uranium from the FSU in the United States and Europe. In Canada, permitting activities continued on the Cigar Lake and McArthur River projects; and construction commenced on the McClean Lake mill.

6 6 Notes: Gasoline pump prices have backed down from the high prices experienced last summer and fall. The retail price for regular motor gasoline fell 11 cents per gallon from September to December. However, with crude oil prices rebounding somewhat from their December lows combined with lower than normal stock levels, we project that prices at the pump will rise modestly as the 2001 driving season begins this spring. For the summer of 2001, we expect only a little difference from the average price of $1.50 per gallon seen during the previous driving season, as motor gasoline stocks going into the driving season are projected to be slightly less than they were last year. The situation of relatively low inventories for gasoline could set the stage for some regional imbalances in supply that could once again

This chart highlights residential heating oil prices for the current and This chart highlights residential heating oil prices for the current and past heating season. As you can see, prices have started the heating season, about 40 to 50 cents per gallon higher than last year at this time. The data presented are from EIA's State Heating Oil and Propane Program. We normally collect and publish this data twice a month, but given the low stocks and high prices, we started tracking the prices weekly. These data will also be used to determine the price trigger mechanism for the Northeast Heating Oil Reserve. The data are published at a State and regional level on our web site. The slide is to give you some perspective of what is happening in these markets, since you probably will get a number of calls from local residents about their heating fuels bills

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A new framework for asset price dynamics is introduced in which the concept of noisy information about future cash flows is used to derive the price processes. In this framework an asset is defined by its cash-flow structure. Each cash flow is modelled by a random variable that can be expressed as a function of a collection of independent random variables called market factors. With each such "X-factor" we associate a market information process, the values of which are accessible to market agents. Each information process is a sum of two terms; one contains true information about the value of the market factor; the other represents "noise". The noise term is modelled by an independent Brownian bridge. The market filtration is assumed to be that generated by the aggregate of the independent information processes. The price of an asset is given by the expectation of the discounted cash flows in the risk-neutral measure, conditional on the information provided by the market filtration. When the cash flows are th...

In this paper we consider the problem of a firm that faces a stochastic (Poisson) demand and must replenish from a market in which prices fluctuate, such as a commodity market. We describe the price evolution as a continuous stochastic process and we ... Keywords: production/inventory

This report is part of an annual series that presents current and historical information on the production, trade, consumption, and prices of timber products in the United States. The report focuses on national statistics, but includes some data for individual States and regions and for Canada. The data were collected from industry trade associations and government agencies. They are intended for use by forest land managers, forest industries, trade associations, forestry schools, renewable resource organizations, libraries, organizations, individuals in the major timber producing and consuming countries of the world, and the general public. A major use of the data presented here is tracking technological change over time. One of the major technology shifts occurring in the wood-using industry is the substitution of oriented strandboard (OSB) for plywood in the structural panel sector, as well as a shift in plywood production from the west to the south United States. Some data show these shifts. United States production of structural panels totaled 29.4 billion ft in 1999. Production of OSB increased from less than 3 billion ft in 1985 to 11.6 billion ft in 1999. Plywood production was 20.1 billion ft in 1985 before falling to 17.8 billion ft in 1999. The decline in plywood production reflects the continued increase in the OSB share of the traditional plywood market

A steady increase in oil imports leaves oil importing countries increasingly vulnerable tofuture oil price shocks. Using a variation of the U.S. EIA`s oil market simulation model, equilibria displaying multiple price shocks is derived endogenously as a result of optimizing behavior on the part of OPEC. Here we investigate the effects that an oil import tariff and a petroleum stock release policy may have on an OPEC optimal price path. It is shown that while both policies can reduce the magnitude of futureprice shocks neither may be politically or technically feasible. 21 refs., 7 figs., 6 tabs.

This report is concerned with the financial risks that arise from the uncertain price of transmission service in restructured or competitive electricity markets. These risks are most severe in markets with locational pricing (LMP), but they also exist in more traditionally organized electricity markets. This report has two main purposes. The first is to review the existing mathematical models of electricity price formation in spot and forward markets that may be helpful as the foundations for developing ...

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), the simulation day, and the linear trend of selling prices from the previous ten days. For predicting futureprices, we used the same set of features with the addition of the estimated customer demand trend (s). 4Forecasting market prices in a supply chain game q Christopher Kiekintveld a,*, Jason Miller b

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This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futuresprice. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futuresprice provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futuresprice underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futuresprice into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

The price of crude oil in the U.S. never exceeded $40 per barrel until mid-2004. By 2006 it reached $70, and in July 2008 it peaked at $145. By late 2008 it had plummeted to about $30 before increasing to $110 in 2011. Are speculators at least partly to blame for these sharp price changes? We clarify the effects of speculators on commodity prices. We focus on crude oil, but our approach can be applied to other commodities. We explain the meaning of “oil price speculation, ” how it can occur, and how it relates to investments in oil reserves, inventories, or derivatives (such as futures contracts). Turning to the data, we calculate counterfactual prices that would have occurred from 1999 to 2012 in the absence of speculation. Our framework is based on a simple and transparent model of supply and demand in the cash and storage markets for a commodity. It lets us determine whether speculation is consistent with data on production, consumption, inventory changes, and convenience yields given reasonable elasticity assumptions. We show speculation had little, if any, effect on prices and volatility.

Increased competition in bulk power and retail electricity markets is likely to lower electricity prices, but will also result in greater price volatility as the industry moves away from administratively determined, cost-based rates and encourages market-driven prices. Price volatility introduces new risks for generators, consumers, and marketers. Electricity futures and other derivatives can help each of these market participants manage, or hedge, price risks in a competitive electricity market. Futures contracts are legally binding and negotiable contracts that call for the future delivery of a commodity. In most cases, physical delivery does not take place, and the futures contract is closed by buying or selling a futures contract on or near the delivery date. Other electric rate derivatives include options, price swaps, basis swaps, and forward contracts. This report is intended as a primer for public utility commissioners and their staff on futures and other financial instruments used to manage price risks. The report also explores some of the difficult choices facing regulators as they attempt to develop policies in this area.

Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

We outline initial concepts for an immune inspired algorithm to evaluate and predict oil price time series data. The proposed solution evolves a short term pool of trackers dynamically, with each member attempting to map trends and anticipate futureprice movements. Successful trackers feed into a long term memory pool that can generalise across repeating trend patterns. The resulting sequence of trackers, ordered in time, can be used as a forecasting tool. Examination of the pool of evolving trackers also provides valuable insight into the properties of the crude oil market.

The objective of the present spot pricing study carried out for SCE and PG&E is to develop the concepts which wculd lead to an experimental design for spot pricing in the two utilities. The report suggests a set of experiments ...

Generators supplying electricity markets are subject to volatile input and output prices and uncertain fuel availability. Price-risk may be hedged to a considerable extent but fuel-risk — water flows in the case of hydro and gas availability in the case of thermal plants — may not be. We show that a price-taking generator will only generate when the output price exceeds its marginal cost by an amount that reflects the value of the option to delay the use of stored fuel. The corresponding offer price is different from the theorized offer prices of static uniform auctions and more akin to pay-as-bid auction prices. We argue that the option value of delaying fuel use, which is an increasing function of spot price volatility and the uncertainty about fuel availability, must be considered when evaluating whether market power is present in electricity markets. The engineering approach to simulating an electricity supply curve, which has been used in market power evaluations to date, may lead to supply curves that are quite different from those that recognize possible fuel availability limitations, even in the complete absence of market power.